This invention relates generally to the field of computer networks and more specifically to quality of service provisioning within a computer network.
A network domain may have a special network server, herein termed a bandwidth broker, responsible for maintaining the network Quality of Service (QoS) states and performing various QoS control and management functions such as admission control, resource reservation and provisioning for the entire network domain. A centralized bandwidth broker for the control and management of QoS provisioning may reduce the complexity of a QoS control plane.
A centralized bandwidth broker for QoS control and management has several appealing features. For example, a centralized bandwidth broker may decouple a QoS control plane from a data plane. In particular, QoS control functions such as admission control and QoS state maintenance are removed from the core routers of a network domain located within the data plane, thus reducing the complexity of the core routers. Consequently, hop-by-hop signaling for reservation set-up along the path may be eliminated, thus removing signaling overhead from the core routers. Furthermore, because network QoS states may be centrally managed by the bandwidth broker, the problems of unreliable or inconsistent control states may be circumvented. In this respect, a centralized bandwidth broker may provide a scalable alternative for QoS control and management.
However, a centralized bandwidth broker for QoS control and management also introduces its own scalability issue, in particular, the ability of a bandwidth broker to handle large volumes of flows as the network system scales. In a network where only slow time scale, static resource provisioning and traffic engineering (e.g., those performed to set up virtual private networks) are performed, the scalability problem may not be acute. But with the rapid evolution of today's Internet, many new applications and services such as Voice over IP (VoIP), on-demand media streaming and real-time content delivery (e.g., stock quotes and news) may require dynamic QoS control and management such as admission control and resource provisioning at the time scale of flow arrival and departure. In these circumstances, an inappropriately centralized bandwidth broker system can become a potential bottleneck, limiting the number of flows that can be accommodated into the network system, while the network system itself is still under-loaded.
One measure of scalability is the ability of a bandwidth broker system to handle large volumes of flow reservation requests, as the network system increases in size. For example, as the network link capacity increases, the call processing capability of a bandwidth broker system, herein defined as the number of flow requests that can be processed by the bandwidth broker system per unit of time, should increase proportionally with increasing numbers of flows that can be accommodated in the network system. In particular, a bandwidth broker should not become a bottleneck while the network system has not been overloaded.
Although it may be possible to enhance the call processing capability of a bandwidth broker by simply adding more processing power or increasing memory and disk access speed, such an approach in itself may not provide a scalable bandwidth broker. There are many factors that may potentially affect the call processing capability of a bandwidth broker. Among them, the speed of memory and disk accesses may play a prominent role. When processing a flow reservation set-up request, a bandwidth broker performs an admissibility test, and if the request can be granted, the bandwidth broker updates the relevant QoS states. Likewise, when processing a flow reservation tear-down request, a bandwidth broker updates the relevant QoS states. In either case, access and/or update to QoS states are involved. Since memory/disk access speed is typically much slower than processing speed, the processing time of flow requests may be determined in a large part by the number of memory/disk accesses and updates.
Another factor that may affect the overall call processing capability of a centralized bandwidth broker is the capacity of the communication channels (e.g., the network or I/O bandwidth) between a centralized bandwidth broker and various edge routers. As the number of flows increases, these communication channels may become a bottleneck, limiting the number of flow requests delivered to a centralized bandwidth broker system, thereby reducing a centralized bandwidth broker's overall call processing capability. To scale with the demand of the network system, a distributed multiple-bandwidth-broker architecture may be called for.